scholarly journals Attitudes about Brain–Computer Interface (BCI) technology among Spanish rehabilitation professionals

AI & Society ◽  
2021 ◽  
Author(s):  
Aníbal Monasterio Astobiza ◽  
David Rodriguez Arias-Vailhen ◽  
Txetxu Ausín ◽  
Mario Toboso ◽  
Manuel Aparicio ◽  
...  

AbstractTo assess—from a qualitative perspective—the perceptions and attitudes of Spanish rehabilitation professionals (e.g. rehabilitation doctors, speech therapists, physical therapists) about Brain–Computer Interface (BCI) technology. A qualitative, exploratory and descriptive study was carried out by means of interviews and analysis of textual content with mixed generation of categories and segmentation into frequency of topics. We present the results of three in-depth interviews that were conducted with Spanish speaking individuals who had previously completed a survey as part of a larger, 3-country/language, survey on BCI perceptions. 11 out of 15 of these Spanish respondents (survey) either strongly or somewhat accept the use of BCI in rehabilitation therapy. However, the results of our three in-depth interviews show how, due to a strong inertia of attitudes and perceptions about BCI technology, most professionals feel reluctant to use BCI technology in their daily practice (interview).

2013 ◽  
Vol 133 (3) ◽  
pp. 635-641
Author(s):  
Genzo Naito ◽  
Lui Yoshida ◽  
Takashi Numata ◽  
Yutaro Ogawa ◽  
Kiyoshi Kotani ◽  
...  

Author(s):  
Selma Büyükgöze

Brain Computer Interface consists of hardware and software that convert brain signals into action. It changes the nerves, muscles, and movements they produce with electro-physiological signs. The BCI cannot read the brain and decipher the thought in general. The BCI can only identify and classify specific patterns of activity in ongoing brain signals associated with specific tasks or events. EEG is the most commonly used non-invasive BCI method as it can be obtained easily compared to other methods. In this study; It will be given how EEG signals are obtained from the scalp, with which waves these frequencies are named and in which brain states these waves occur. 10-20 electrode placement plan for EEG to be placed on the scalp will be shown.


2014 ◽  
Vol 39 (3) ◽  
pp. 208-221 ◽  
Author(s):  
Xing-Yu WANG ◽  
Jing JIN ◽  
Yu ZHANG ◽  
Bei WANG

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